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How to Distinguish Contaminants from Pathogens in Blood Cultures

Summary: Analysis of 38,216 peripheral blood culture sets indicates that discordant versus concordant bottle positivity provides a practical and effective means of differentiating contamination from true bacteremia.
A practical approach to reducing false positive blood cultures
Differentiate Sample Contamination and From True Bacteremia With Replicate Blood Cultures

Why This Matters:

  • Blood culture contamination (BCC) is common: skin flora such as coagulase-negative staphylococci (CoNS) introduced at the time of venipuncture are the most common cause of blood culture contamination in most clinical settings. Contaminated cultures increase diagnostic uncertainty, prolong hospital stays, and drive unnecessary antimicrobial use.
  • Early differentiation aids stewardship: Rapid distinction between contaminants and true pathogens supports antimicrobial stewardship by reducing inappropriate therapy and associated harms.
  • Growth pattern analysis is accessible: Simple interpretation of whether organisms grow in one vs. both bottles can provide clinically actionable information within 24 hours of culture positivity.

Key Findings:  The authors retrospectively analyzed 38,216 blood culture sets collected by peripheral venipuncture from 2019 to 2024 by assessing growth patterns (growth in one bottle [discordant] vs growth in both bottles [concordant]) in relation to clinical significance (contaminant vs true pathogen).1

  • Concordant vs. discordant growth: Discordant sets (growth in only one of a paired aerobic/anaerobic bottle) comprised 1,491 sets (3.9%); concordant sets (growth in both bottles) comprised 1,938 sets (5.1%), with the remainder sterile.
  • Contaminants predominated in discordant growth: 71.1% of discordant sets were contaminants vs. 11.4% of concordant sets (P<0.001). True pathogens were more prevalent in concordant growth.
  • Coagulase-negative staphylococci (CoNS): In the CoNS subgroup, 98.0% of discordant sets represented contamination, while only 2.0% reflected true CoNS bacteremia. Discordant first CoNS cultures had a negative predictive value (NPV) of 98.1% (95% CI 96.7%–98.9%) for ruling out true CoNS bacteremia.
  • Aerobic vs. anaerobic bottles: Contaminants were observed more frequently in aerobic bottles (37.9%) than anaerobic ones (20.5%). The proportion of true pathogens did not differ significantly between bottle types.
  • Clinical implication: Discordant growth — especially for CoNS — is highly predictive of contamination, and growth pattern analysis can inform early interpretation and support antimicrobial stewardship decisions within 24 hours.

Bigger Picture:   This study validates a simple, pragmatic diagnostic marker — whether an organism grows in one versus both blood culture bottles — as a reliable discriminator between contaminants and true pathogens, particularly for skin commensals like CoNS. Given the frequency of blood culture contamination and its downstream consequences (unnecessary antibiotics, extended hospital stays, and increased costs), integrating growth pattern analysis into clinical workflows can improve diagnostic accuracy and antimicrobial stewardship. This approach complements other strategies (e.g., time-to-positivity, clinical risk stratification) and enhances early interpretation without requiring additional laboratory resources. 

(Image Credit: iStock/Scharvik) 

References:

  1. Ben-Chetrit et al. 2025. Diagnostic Value of Blood Culture Growth Patterns in Distinguishing Contaminants from Pathogens. Journal of Clinical Microbiology.